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DEVELOPMENT OF RFID POSITIONING SYSTEM USING NEURAL NETWORK MODEL

机译:基于神经网络模型的RFID定位系统的开发

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摘要

In this paper, an overview of the RFID system which aims to measure position of RF tags covering wide area is presented.We propose a measuring method which uses relation between reaction strength from multi-antennas and RF tags' 2D coordinate.We put antennas at intervals of 1.0 m to 2.0 m to read RF tags by multiple antennas and specify RF tags' position by the reaction pattern.To increase the accuracy of measuring, we adapted neural network modeling and we tested various conditions to inspect the best model which minimize error of the measurement.Operation tests had been conducted at approximately 100 m2 room with 11 antennas and dynamic objects and static objects were tested.As a result we confirmed that our RFID system can measure RFID tags within 0.4 m error for dynamic objects and 0.5 m for static objects.
机译:本文概述了旨在测量覆盖广泛区域的RF标签位置的RFID系统。我们提出了一种利用多天线的反应强度与RF标签的2D坐标之间的关系进行测量的方法。间隔为1.0 m到2.0 m以通过多个天线读取RF标签并通过反应模式指定RF标签的位置。为了提高测量的准确性,我们采用了神经网络建模方法,并测试了各种条件以检查最佳模型以最大程度地减少误差我们已经在大约100平方米的房间内使用11根天线进行了操作测试,并测试了动态物体和静态物体,结果我们确认我们的RFID系统可以测量动态物体误差在0.4 m以内的RFID标签,对于动态物体误差在0.5 m以内静态对象。

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